A simple method of tuning parallel cascade controllers for unstable FOPTD systems

A simple method is proposed to design parallel cascade controllers for open loop unstable processes. A proportional (P)controller is considered for the secondary loop and a proportional integral (PI) controller is considered for the primary loop (P/PI control configuration). Coefficients of the corresponding powers of s (Laplace variable), in the numerator is matched with the coefficients of the corresponding powers of s in the denominator of a closed loop transfer function for a servo problem. Three simulation case studies are considered in this paper. The first case involves a stable secondary loop process and an unstable primary process, the second case involves both unstable primary and secondary processes and the third one, a simulation application to a nonlinear bioreactor model equations. For comparison purposes, P/PI controller design is also carried out by improved simultaneous relay autotuning method, synthesis method and minimizing ISE criterion method. It is found that the proposed method gives a better performance. Robust stability analysis using the complimentary sensitivity function is carried out. The present method is found to be more robust.     

Disturbance-rejection-based tuning of proportional–integral–derivative controllers by exploiting closed-loop plant data

A systematic data-based design method for tuning proportional–integral–derivative (PID) controllers for disturbance attenuation is proposed. In this method, a set of closed-loop plant data are directly exploited without using a process model. PID controller parameters for a control system that behaves as closely as possible to the reference model for disturbance rejection are derived. Two algorithms are developed to calculate the PID parameters. One algorithm determines the optimal time delay in the reference model by solving an optimization problem, whereas the other algorithm avoids the nonlinear optimization by using a simple approximation for the time delay term, enabling derivation of analytical PID tuning formulas. Because plant data integrals are used in the regression equations for calculating PID parameters, the two proposed algorithms are robust against measurement noises. Moreover, the controller tuning involves an adjustable design parameter that enables the user to achieve a trade-off between performance and robustness. Because of its closed-loop tuning capability, the proposed method can be applied online to improve (retune) existing underperforming controllers for stable, integrating, and unstable plants. Simulation examples covering a wide variety of process dynamics, including two examples related to reactor systems, are presented to demonstrate the effectiveness of the proposed tuning method.     

Optimal disturbance rejection for PI controller with constraints on relative delay margin

Performance optimization with robustness constraints is frequently encountered in process control. Motivated by the analytical difficulties in dealing with the conventional robustness index, e.g., maximum sensitivity, we introduce the relative delay margin as a good alternative, which gives much simpler robust analysis. This point is illustrated by designing an optimal PI controller for the first-order-plus-dead-time (FOPDT) model. It is first shown that the PI controller parameters can be analytically derived in terms of a new pair of parameters, i.e., the phase margin and gain crossover frequency. The stability region of PI controller is subsequently obtained with a much simpler procedure than the existing approaches. It is further shown that a certain relative delay margin can represent the robustness level well and the contour can be sketched with a simpler procedure than the one using maximum sensitivity index. With constraints on the relative delay margin, an optimal disturbance rejection problem is then formulated and analytically solved. Simulation results show that the performance of the proposed methodology is better than that of other PI tuning rules. In this paper, the relative delay margin is shown as a promising robustness measure to the analysis and design of other advanced controllers.     

一类时滞系统的PID稳定控制器设计

针对工业控制过程中常见的时滞系统,给出了快速计算PI和PID控制器所有稳定参数集的方法。推导了系统开环不稳定情形下稳定控制器存在的必要性条件．通过在该稳定参数区域上进行性能指标寻优,可以得到满足控制器设计性能指标要求的PID控制器参数区域。仿真实例表明了该方法的优越性。     

离散制造系统中比例积分控制器的应用与工程实现

将比例积分控制应用于离散制造系统在制品库存控制。以加工工段间在制品为研究对象,建立了离散制造系统在制品之PI控制的级联控制模型。同时将PI控制器参数的选择转化为频域上的优化问题,以保证其稳定性和鲁棒性。设计了积压任务控制器和输入速率控制器,分别对应PI控制的积分控制和比例控制,解决了PI控制器的工程实现问题。仿真结果表明,实现后的PI控制器具有良好的控制效果。     

多变量协调自适应控制器初步研究

本文初步研究了多变时过程控制器设计的优化目标和约束的统一表达体系,将模块多变量控制技术引入自适应控制器的设计过程,提出了多变量协调自适应控制器的概念,并初步解决了有约束的多目标优化控制的设计问题。     

Model predictive control for a class of systems with isolated nonlinearity

The paper is concerned with an overall convergent nonlinear model predictive control design for a kind of nonlinear mechatronic drive systems. The proposed nonlinear model predictive control results in the improvement of regulatory capacity for reference tracking and load disturbance rejection. The design of the nonlinear model predictive controller consists of two steps: the first step is to design a linear model predictive controller based on the linear part of the system at each sample instant, then an overall convergent nonlinear part is added to the linear model predictive controller to combine a nonlinear controller using error driven. The structure of the proposed controller is similar to that of classical PI optimal regulator but it also bears a set-point feed forward control loop, thus tracking ability and disturbance rejection are improved. The proposed method is compared with the results from recent literature, where control performance under both model match and mismatch cases are enlightened.     

A new design method for PI–PD control of unstable processes with dead time

PID controllers are still widely practiced in the industrial systems. In the literature, many publications can be found considering PID controller design for unstable processes. However, owing to the structural limitations of PID controllers, generally, good closed loop performance cannot be achieved with a PID for controlling unstable processes and usually a step response with a high overshoot and oscillation is obtained. On the other hand, PI–PD controllers are proved to give very satisfactory closed loop performances for unstable processes. The paper presents a simple design method to tune parameters of a PI–PD controller for the control of the unstable processes with time delay. The proposed method is based on plotting the stability boundary locus, which is a locus dependent on the parameters of the controller and frequency, in the parameter plane. The method uses a new concept named centroid of the convex stability region. Simulation examples and an experimental application are given to illustrate the superiority of the proposed method over some existing ones.     

Enhanced IMC design of load disturbance rejection for integrating and unstable processes with slow dynamics

In view of the deficiencies in existing internal model control (IMC)-based methods for load disturbance rejection for integrating and unstable processes with slow dynamics, a modified IMC-based controller design is proposed to deal with step- or ramp-type load disturbance that is often encountered in engineering practices. By classifying the ways through which such load disturbance enters into the process, analytical controller formulae are correspondingly developed, based on a two-degree-of-freedom (2DOF) control structure that allows for separate optimization of load disturbance rejection from setpoint tracking. An obvious merit is that there is only a single adjustable parameter in the proposed controller, which in essence corresponds to the time constant of the closed-loop transfer function for load disturbance rejection, and can be monotonically tuned to meet a good trade-off between disturbance rejection performance and closed-loop robust stability. At the same time, robust tuning constraints are given to accommodate process uncertainties in practice. Illustrative examples from the recent literature are used to show effectiveness and merits of the proposed method for different cases of load disturbance.     

Relay-enhanced multi-loop PI controllers

In this paper, the development of relay-enhanced multi-loop PI controllers is described for multivariable processes. The control system employs a relay in series with the controller. The relay can ensure a satisfactory level of closed-loop performance and it also yields oscillations for tuning of the PI controller based on an equivalent process model for each loop. A simulation example [on a two-inputs-two-outputs (TITO) process] is provided to illustrate the effectiveness of the proposed method and to compare its performance to an existing method.     

A novel composite adaptive flap controller design by a high-efficient modified differential evolution identification approach

The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases.     

Self-organizing fuzzy control of constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have nonlinear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate ones real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for constant cutting force control to evaluate control performance of the turning system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the turning process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in turning systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The SOFC has a better control performance in constant cutting force control than does the TFC, as verified in experimental results.     

变结构PI控制器的设计及其在光电跟踪系统中的应用

为了给光电跟踪系统提供高性能的伺服控制,基于传统的PI控制器原理,结合变结构的思想,设计了一种变结构PI控制器(VSPI)。介绍了该控制器的工作原理并讨论了设计参数的选择。基于某型号光电跟踪系统,分别对采用了VSPI、抗积分饱和PI控制器(AWPI)和积分分离PI控制器(ISPI)作为位置回路控制器的伺服控制系统进行了仿真和实验。实验结果表明,采用了VSPI的光电跟踪系统基本无超调,上升时间为0.378s,稳定时间为0.488s,跟踪精度为1.26″。该系统结构简单,能实现嵌入式实时控制;与其他两种控制器相比综合性能更好,完全满足光电跟踪系统精度高、响应快的要求。     

A novel auto-tuning PID control mechanism for nonlinear systems

In this paper, a novel Runge–Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence.     

Self-organizing fuzzy control of constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have nonlinear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate ones real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for constant cutting force control to evaluate control performance of the turning system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the turning process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in turning systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The SOFC has a better control performance in constant cutting force control than does the TFC, as verified in experimental results.     

CONVEX CONTROLLER DESIGN APPLIED TO AC INDUCTION MOTOR TO SATISFY MULTIPLE SIMULTANEOUS SPECIFICATIONS

The application of a closed-loop specification oriented feedback control design method, which addresses the design of controllers to satisfy multiple simultaneous conflicting closed-loop performance specifications is presented. The proposed approach is well suited to the design of controllers which must meet a set of conflicting performance specifications. Gain tuning is central to the design process, however, the tuning process is greatly simplified over that presented by the problem of tuning a PID controller for example. The proposed control method is applied to an AC induction motor, with an inner-loop flux vector controller applied to design a position control system. Experimental results verify the effectiveness of this method.     

Enhanced disturbance rejection for open-loop unstable process with time delay

The present study suggests a disturbance estimator design method for application to a recently published, two-degree-of-freedom, control scheme for open-loop, unstable processes with time delay. A simple PID controller cascaded with a lead-lag filter replaces the high-order disturbance estimator for enhanced performance. A new analytical method on the basis of the IMC design principle, featuring only one user-defined tuning parameter, is developed for the design of the disturbance estimator. Several illustrative examples taken from previous works are included to demonstrate the superiority of the proposed disturbance estimator. The results confirm the superior performance of the proposed disturbance estimator in both nominal and robust cases. The proposed method also offers several important advantages for industrial process engineers: it covers several classes of unstable process with time delay in a unified manner, and is simple and easy to design and tune.     

Measurement and Control of Process using Soft Computing

Abstract

Control of process parameters is considered to be a critical problem in the process industry. The process considered for modeling is a liquid level system. The model identification and parameter selection are approximated to a First Order Plus Dead Time (FOPDT). Here, the controller design is based on a conventional Proportional–Integral (PI) controller and intelligent controller like Fuzzy Logic Controller (FLC). The objective of the current study is to design control strategies in real time using MATLAB software interfaced with Adam's data acquisition module. A comparative analysis based on FLC with a conventional controller is presented, with various time domain specifications. It is found that, under servo and regulatory changes, FLC shows an improved performance over its conventional techniques based on performance measures like peak time, settling time, overshoot, Integral Square Error (ISE) and Integral Absolute Error (IAE).